Dynamics of Functional Networks for Syllable and Word-Level Processing

Abstract

Abstract Speech comprehension requires the ability to temporally segment the acoustic input for higher-level linguistic analysis. Oscillation-based approaches suggest that low-frequency auditory cortex oscillations track syllable-sized acoustic information and therefore emphasize the relevance of syllabic-level acoustic processing for speech segmentation. How syllabic processing interacts with higher levels of speech processing, beyond segmentation, including the anatomical and neurophysiological characteristics of the networks involved, is debated. In two MEG experiments, we investigate lexical and sublexical word-level processing and the interactions with (acoustic) syllable processing using a frequency-tagging paradigm. Participants listened to disyllabic words presented at a rate of 4 syllables/s. Lexical content (native language), sublexical syllable-to-syllable transitions (foreign language), or mere syllabic information (pseudo-words) were presented. Two conjectures were evaluated: (i) syllable-to-syllable transitions contribute to word-level processing; and (ii) processing of words activates brain areas that interact with acoustic syllable processing. We show that syllable-to-syllable transition information compared to mere syllable information, activated a bilateral superior, middle temporal and inferior frontal network. Lexical content resulted, additionally, in increased neural activity. Evidence for an interaction of word- and acoustic syllable-level processing was inconclusive. Decreases in syllable tracking (cerebroacoustic coherence) in auditory cortex and increases in cross-frequency coupling between right superior and middle temporal and frontal areas were found when lexical content was present compared to all other conditions; however, not when conditions were compared separately. The data provide experimental insight into how subtle and sensitive syllable-to-syllable transition information for word-level processing is.